DAC Nonlinearity Measurement Using Pseudo-Random Code Ordering
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Solution Overview
Problem
The precision of DAC nonlinearity error measurement is adversely affected by temperature changes due to the strong coupling relationship between DAC code values and temperature, leading to high measurement costs when using thermostatic devices for stabilization.
Innovation Solution
A method using a pseudo-random sequence to number DAC code values, determining differential and integral nonlinearity errors by arranging pseudo-random number values in a serial order, and calculating error arrays to separate temperature-induced errors, thereby improving measurement precision without high-cost thermostatic devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-precision voltmeter or programmable standard voltage source is used to measure DAC nonlinearity errors step by step, then measurement accuracy can be improved, but temperature changes during sequential code output cause measurement precision to deteriorate
Solution Approach 1:
The patent applies periodic action by using a pseudo-random sequence to repeatedly cycle through all DAC code values multiple times. Instead of measuring each code value once in sequential order, the system cycles through the entire code range repeatedly with randomization, allowing temperature drift effects to be averaged out across multiple measurement cycles, thereby improving measurement reliability under temperature variation
Solution Approach 2:
The patent inverts the traditional measurement approach by randomizing the output order of DAC code values using a pseudo-random sequence. Rather than outputting code values in sequential order (0, 1, 2, ..., 2^n-1), the system outputs them in random order across multiple cycles, which decouples the strong correlation between code value and temperature, thereby improving measurement precision
2Measurement precision
If a thermostatic device is used to provide a high-stability temperature environment and prolong stabilization time, then measurement precision is improved, but the cost of the measurement system increases significantly
Solution Approach 1:
The patent replaces the mechanical/physical thermostatic control system with a software-based pseudo-random sequence generation and data processing system. Instead of using complex hardware temperature control devices to maintain thermal stability, the system uses algorithmic randomization to measure and correct for temperature effects, significantly reducing device complexity and cost while maintaining measurement precision
Solution Approach 2:
The patent changes the measurement parameter from sequential code ordering to pseudo-random code ordering. By transforming the deterministic sequential measurement sequence into a random sequence, the system fundamentally changes how temperature effects manifest in the measurements, allowing post-processing to separate and eliminate temperature-induced errors without requiring active temperature control hardware
Data Source
AI summary
Provided is a method for measuring a DAC nonlinearity error based on a pseudo-random sequence. The method includes: numbering pseudo-random number values in a pseudo-random sequence to generate a serial number sequence; arranging the pseudo-random number values in the serial number sequence in a descending or ascending order to determine an order random array; sending the pseudo-random number values, as DAC code values, in the order random array to the DAC sequentially; determining a first differential voltage array and a second differential voltage array according to a voltage corresponding to the DAC code values and the DAC code values; and determining a nonlinearity error measurement result of the DAC according to a differential nonlinearity error test result of the DAC and an integral nonlinearity error test result of the DAC determined by the first differential voltage array and the second differential voltage array.